关于python：安装gensim时的Chunkize警告

Chunkize warning while installing gensim

我在Python中安装了gensim(通过pip)。安装结束后，我收到以下警告：

C:\Python27\lib\site-packages\gensim\utils.py:855: UserWarning: detected Windows; aliasing chunkize to chunkize_serial
warnings.warn("detected Windows; aliasing chunkize to chunkize_serial")

我怎么能纠正这个？

由于此警告，我无法从gensim.models导入word2vec。

我有以下配置：Python 2.7，gensim-0.13.4.1，numpy-1.11.3，scipy-0.18.1，pattern-2.6。

在导入gensim之前，您可以使用此代码禁止显示消息：

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import warnings
warnings.filterwarnings(action='ignore', category=UserWarning, module='gensim')

import gensim

相关讨论

我认为这不是一个大问题。 Gensim只是让你知道它会将chunkize别名化为不同的函数，因为你使用了特定的操作系统。

从gensim.utils查看此代码

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if os.name == 'nt':
logger.info("detected Windows; aliasing chunkize to chunkize_serial")

def chunkize(corpus, chunksize, maxsize=0, as_numpy=False):
for chunk in chunkize_serial(corpus, chunksize, as_numpy=as_numpy):
yield chunk
else:
def chunkize(corpus, chunksize, maxsize=0, as_numpy=False):
"""
Split a stream of values into smaller chunks.
Each chunk is of length `chunksize`, except the last one which may be smaller.
A once-only input stream (`corpus` from a generator) is ok, chunking is done
efficiently via itertools.

If `maxsize > 1`, don't wait idly in between successive chunk `yields`, but
rather keep filling a short queue (of size at most `maxsize`) with forthcoming
chunks in advance. This is realized by starting a separate process, and is
meant to reduce I/O delays, which can be significant when `corpus` comes
from a slow medium (like harddisk).

If `maxsize==0`, don't fool around with parallelism and simply yield the chunksize
via `chunkize_serial()` (no I/O optimizations).

>>> for chunk in chunkize(range(10), 4): print(chunk)
[0, 1, 2, 3]
[4, 5, 6, 7]
[8, 9]

"""
assert chunksize > 0

if maxsize > 0:
q = multiprocessing.Queue(maxsize=maxsize)
worker = InputQueue(q, corpus, chunksize, maxsize=maxsize, as_numpy=as_numpy)
worker.daemon = True
worker.start()
while True:
chunk = [q.get(block=True)]
if chunk[0] is None:
break
yield chunk.pop()
else:
for chunk in chunkize_serial(corpus, chunksize, as_numpy=as_numpy):
yield chunk